Global Environmental Microelectromechanical Systems Sensors: Advanced Weather Observation System

The technological developments in microelectromechanical systems (MEMS) have resulted in conceptualisation of a next generation observation system called global environmental MEMS sensors (GEMS). GEMS consists of a large number of airborne probes that will remain suspended in the atmosphere for long durations and take in situ measurements of pressure, temperature, humidity, wind direction and velocity as these are carried by air currents. It is envisaged that GEMS network would provide a systematic understanding of the earths atmosphere and would improve weather forecast accuracy, well beyond the current capability. In addition to gathering meteorological data, probes could be used for environmental monitoring of particulate emissions, organic and inorganic pollutants, ozone, carbon dioxide, and chemical, biological, or nuclear contaminants. The GEMS concept requires integration of communication engineering and instrumentation with other evolving technologies. This review describes in detail the new observation system designed for environmental monitoring and its potential application in predicting cyclones and monsoon, and measurement of urban air pollution in India. The possible application of the GEMS system during military operations has also been brought out.Defence Science Journal, 2009, 59(6), pp.659-665, DOI:http://dx.doi.org/10.14429/dsj.59.157

Case report of a rare case of meibomian gland carcinoma of the lower eyelid

The sebaceous gland carcinoma is a very rare, highly malignant tumour of the eyelid arising from sebaceous glands of the eyelid such as meibomian glands, glands of Zeis, and caruncle. The tumour is more commonly seen in elderly females and more commonly involve the upper eyelid. We present a rare case of meibomian gland carcinoma of the left lower eyelid in a 59-year-old female who came with a history of a slow growing painless swelling of the lower eyelid. Histopathological examination confirmed poorly differentiated meibomian gland carcinoma

Thyroid ophthalmopathy in an adolescent girl: a case report

A 14 year old girl presented with protrusion of both the eyes for duration of 3 months and pain, redness and watering of right eye for 20 days. On examination, she was thin built, poorly nourished and the thyroid gland was found to be enlarged. Both eyes were proptosed and there was incapability of complete closure of the eyelids on both sides. On right eye, conjunctiva was congested and there was a corneal lesion seen inferomedially with an epithelial defect. CT scan of the orbit revealed picture of thyroid ophthalmopathy. Thyroid profile revealed picture suggestive of hyperthyroidism and anti-thyroid peroxidase antibody was found to be very high. She was diagnosed as a case of thyroid ophthalmopathy both eyes with exposure keratitis right eye. She was treated with anti-thyroid medication along with conservative treatment for ocular symptoms and lateral tarsorrhaphy of right eye for exposure keratopathy. Pulse steroid therapy was started and subsequent follow up showed resolution of the signs

A case of bilateral acute angle closure attack with some unusual features

A 45 year old male presented with sudden severe pain, redness and marked diminution of vision in both eyes along with corneal oedema, pigmented KPs and raised IOP. After treatment with hyper osmotic agents, IOP came down and cornea became clear. Anterior chamber was shallow bilaterally with ring synechia. Gonioscopy revealed peripheral anterior synechiae in left eye and occludable angle in the right eye. Fundus examination was within normal limit. The patient was treated with antiglaucoma medications and steroid. Trabeculectomy was done in left eye with laser PI in the fellow eye. IOP came down within normal limits on subsequent visits with residual iris sphincter damage

A Bayesian Perspective of Statistical Machine Learning for Big Data

Statistical Machine Learning (SML) refers to a body of algorithms and methods by which computers are allowed to discover important features of input data sets which are often very large in size. The very task of feature discovery from data is essentially the meaning of the keyword `learning' in SML. Theoretical justifications for the effectiveness of the SML algorithms are underpinned by sound principles from different disciplines, such as Computer Science and Statistics. The theoretical underpinnings particularly justified by statistical inference methods are together termed as statistical learning theory. This paper provides a review of SML from a Bayesian decision theoretic point of view -- where we argue that many SML techniques are closely connected to making inference by using the so called Bayesian paradigm. We discuss many important SML techniques such as supervised and unsupervised learning, deep learning, online learning and Gaussian processes especially in the context of very large data sets where these are often employed. We present a dictionary which maps the key concepts of SML from Computer Science and Statistics. We illustrate the SML techniques with three moderately large data sets where we also discuss many practical implementation issues. Thus the review is especially targeted at statisticians and computer scientists who are aspiring to understand and apply SML for moderately large to big data sets.Comment: 26 pages, 3 figures, Review pape